5 Years Away

AGI has been "5 years away" for the past decade. The Tesla Roadster? Five years away since 2014. Tesla's Level 5 self-driving? Promised by 2017, then quietly pushed into the perpetual five-year window. If you've been paying attention, you've probably noticed this pattern extends far beyond Silicon Valley.

Why do we keep landing on this specific timeframe?

Psychologically, five years is close enough to feel relevant. We can easily imagine ourselves five years from now, still affected by these innovations. Yet it's distant enough to seem plausible for ambitious goals. More importantly, it's far enough away that by the time five years passes, people have often moved on or forgotten the original prediction.

This isn't limited to consumer electronics. Medical breakthroughs regularly make headlines with the same promise: a revolutionary cancer treatment, five years away. Carbon nanotubes will transform renewable energy, five years. Solid-state batteries will solve range anxiety... five years.

Andrew Ng, in his course "AI for Everyone," offered the most honest perspective on AGI I've ever read. He suggested it might be decades, hundreds, or even thousands of years away. Why? Before we can meaningfully predict a timeline, we need several fundamental technological breakthroughs that we haven't achieved yet. Without those foundational advances, there's nothing to build on top of.

With all the "5 years away" predictions there is an assumption of linear progress. But the reality is that any transformative technologies require non-linear leaps. They require discoveries we can't yet foresee, solving problems we don't yet fully understand.

A Better Framework

If we want our predictions to mean something, we need a clearer framework. At a minimum, a technology can be labeled "5 years away" only if we have a demonstrated proof of concept, even if it is at a small scale. We need to have identified the major engineering challenges remaining. There should be reasonable pathways to overcome those challenges with existing knowledge. And finally, there needs to be a semblance of economic viability on the horizon.

Anything less than this is speculation dressed up as prediction. If I say that "we've built a prototype that works in the lab, now we need to scale manufacturing", this may in fact be five years away. But when I say "We need multiple fundamental breakthroughs in physics before this is even possible." Here, I am in a science fiction timeline.

Why This Matters

It's not entirely harmless to have inflated predictions. Government policy may be planned around those decisions, they can distort investment decisions, and worse it gives the public false expectations. When we promise self-driving cars by 2017 and fail to deliver, it erodes trust not just in that company, but in the entire field. When every medical breakthrough is "5 years away," people become cynical about real advances.

The "5 years away" framing can make us complacent. If fusion power is always just around the corner, why invest heavily in less glamorous but available renewable technologies today? If AGI will solve everything soon, why worry about the limitations and harms of current AI systems?

It's not the most pressing problem in the world, but wouldn't it be better to have more realistic predictions? When reading news articles about any technology, try to distinguish the difference between engineering challenges and scientific unknowns. A realistic prediction will be explicit by saying things like "This will be ready in 5 years, assuming we solve X, Y, and Z."

The public needs to learn to celebrate incremental progress as well. When all you read about is moonshots, you dismiss important work being done to improve our everyday lives. And of course, the public should also learn to ignore engagement baits.

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Real innovation is hard enough without pretending we can see further into the future than we actually can. Five years is a number. What matters is the foundation beneath it. Without that foundation, we're not counting down to anything. We're just repeating a comfortable fiction that lets us feel like the future is closer than it really is.

The most honest answer to "When will this technology arrive?" is often the least satisfying: "We don't know yet, but here's what needs to happen first." That answer respects both the complexity of innovation and the intelligence of the audience. Maybe it's time we used it more often.

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